GPU Comparison

Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.

Workstation Verdict

The RTX 2000 Ada Generation has more VRAM (16GB vs 8GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 86% higher (416 GB/s vs 224 GB/s), translating directly to faster inference throughput. The Quadro RTX 4000 is $455 USD cheaper than the RTX 2000 Ada Generation.

Maximum Capacity Reached. Remove a model to add another. (2/2)

VS
NVIDIA
Quadro RTX 4000
Price
$263 USD
VRAM
8 GB GDDR6
Mem. Speed
416 GB/s
FP32 Compute
7.1 TFLOPS
Key Specs Advantage
+100% Memory Bus (256-bit vs 128-bit)
+86% Bandwidth (416 GB/s vs 224 GB/s)
Price
$718 USD
VRAM
16 GB GDDR6
Mem. Speed
224 GB/s
FP32 Compute
12 TFLOPS
Key Specs Advantage
+69% FP32 (TFLOPS) (12 TFLOPS vs 7.1 TFLOPS)
+22% CUDA Cores (2,816 vs 2,304)

Quadro RTX 4000 vs RTX 2000 Ada Generation: In-Depth Breakdown

VRAM: Quadro RTX 4000 vs RTX 2000 Ada Generation

The RTX 2000 Ada Generation carries 16GB of VRAM versus 8GB on the Quadro RTX 4000. VRAM capacity is the primary constraint for running AI models without quantization — a 70B-parameter model in FP16 requires roughly 140GB, and even smaller models benefit from extra headroom. The 8GB advantage here means the RTX 2000 Ada Generation can run larger models natively and handle bigger batch sizes in production.

Inference Speed: Memory Bandwidth

Memory bandwidth determines how quickly data is fed to the compute units — it's the main bottleneck for autoregressive inference (token generation in LLMs). The Quadro RTX 4000 delivers 416 GB/s versus 224 GB/s on the RTX 2000 Ada Generation, a 86% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the Quadro RTX 4000 will produce tokens proportionally faster in bandwidth-bound workloads.

AI Training & Compute

For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The RTX 2000 Ada Generation delivers 12 TFLOPS against 7.1 TFLOPS for the Quadro RTX 4000 — a 69% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX 2000 Ada Generation.

Price & Value

The Quadro RTX 4000 lists from $263 USD, $455 USD less than the RTX 2000 Ada Generation at $718 USD. For budget-constrained teams, the savings may outweigh the spec gap — especially if the smaller card covers your typical workload.

Which should you buy: Quadro RTX 4000 or RTX 2000 Ada Generation?

These cards suit different priorities. Choose the RTX 2000 Ada Generation if fitting larger models in VRAM is your constraint. Choose the Quadro RTX 4000 if your models already fit and you want faster inference throughput from its higher memory bandwidth.

Frequently Asked Questions

Can the Quadro RTX 4000 or RTX 2000 Ada Generation run large language models?

Both can, but the RTX 2000 Ada Generation (16GB) handles larger models without quantization. The Quadro RTX 4000 (8GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Quadro RTX 4000 or the RTX 2000 Ada Generation?

The Quadro RTX 4000 is faster for token generation — its 416 GB/s memory bandwidth vs 224 GB/s on the RTX 2000 Ada Generation is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX 2000 Ada Generation has the advantage at 12 TFLOPS vs 7.1 TFLOPS, making training runs proportionally faster than on the Quadro RTX 4000.

Technical Specifications Comparison

Architecture & Cores

SpecificationQuadro RTX 4000RTX 2000 Ada Generation
ArchitectureTuringAda Lovelace
CUDA Cores (CUDA Cores / CUDA Cores)2,3042,816

Memory

SpecificationQuadro RTX 4000RTX 2000 Ada Generation
VRAM Capacity8 GB16 GB
Memory TypeGDDR6GDDR6
Memory Bus256-bit128-bit
Bandwidth416 GB/s224 GB/s

Connectivity & Power

SpecificationQuadro RTX 4000RTX 2000 Ada Generation
InterfacePCIe 3.0 x16PCIe 4.0 x8
TDP160 W70 W
ReleasedOct 2018Mar 2023

Workstation

SpecificationQuadro RTX 4000RTX 2000 Ada Generation
FP32 (TFLOPS)7.1 TFLOPS12 TFLOPS
ECCYesYes
NVLinkNoNo
Form factorsingle-slotlow-profile